About ai-optimizer
AI Token Optimizer is an MCP server for coding agents that filters framework-related noise from file, search and diagnostic results. It applies detected project packs and ignore rules, including .gitignore, to reduce context sent to models.
Key features
- 01Framework-aware file skipping and line slices
- 02Filtered file listing and content search
- 03LSP diagnostics with focused code windows
- 04Symbol lookup through LSP
- 05Clean terminal output and track token savings
Use cases
- 01Avoid loading generated or irrelevant files
- 02Search a project while respecting ignore rules
- 03Inspect diagnostics with a narrow code excerpt
- 04Check detected frameworks and cumulative savings
MCP support
The MCP server provides optimized file, directory, search, diagnostic and status tools for MCP-speaking coding agents.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y @ai-optimizer/coreAI_OPTIMIZER_LICENSESecretEd25519 JWT license key. Unlocks Pro/Team packs; free tier needs no key.AI_OPTIMIZER_LSPSet to 0 to disable the LSP bridge (optimized_diagnostics).AI_OPTIMIZER_TELEMETRYSet to 'on' to enable anonymous opt-in telemetry. Off by default.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
11Saved tool list · updated 3w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| path | string | Yes | Path to the file, relative to the project root |
| endLine | integer | No | 1-indexed end line (inclusive) |
| startLine | integer | No | 1-indexed start line (inclusive) |
Details
From the project READMEAI Token Optimizer
An MCP server that cuts AI coding-agent token usage by 60–80% via framework-aware context optimization.
AI coding agents read whole files when they need 15 lines. They load *.g.dart,
R.java, node_modules/, and dist/ into context — then do it again next turn.
AI Token Optimizer is a Model Context Protocol
server that intercepts those tool calls and strips framework noise before it
reaches the model.
Works with anything that speaks MCP: Claude Code, Cursor, Cline, Continue, Zed, JetBrains AI, GitHub Copilot agent mode, Antigravity, Windsurf, OpenAI Codex CLI.
Quickstart
npm install -g @ai-optimizer/core
Then point your agent at the ai-optimizer stdio server. For Claude Code, add to
~/.claude/settings.json:
{
"mcpServers": {
"ai-optimizer": {
"command": "ai-optimizer"
}
}
}
Or scaffold the config and preview your savings automatically:
npx @ai-optimizer/init
# "we'd skip 47 files, ~14K tokens/session, ~$0.42/session at Sonnet pricing"
Full per-agent setup (Cursor, others), LSP install, and verification steps live in
packages/core/README.md.
What it does
It registers tools the agent uses instead of its built-in file/dir/error reads:
| Tool | What it saves |
|---|---|
optimized_read_file | Framework-aware skip + optional line slice |
optimized_list_files | Walks the tree applying ignore globs (+ .gitignore) |
optimized_grep | Content search scoped by ignore filters |
optimized_diagnostics | Spawns the right LSP, returns errors + a narrow code window |
read_symbol | LSP workspace/symbol slice instead of a full-file read (Pro/LSP) |
strip_bash_noise | Strips ANSI, npm/maven/gradle progress, JVM warnings |
optimizer_status | Detected frameworks, active packs, cumulative tokens saved |
When a project type is detected (e.g. Python via pyproject.toml), the matching
pack's ignore rules activate automatically. .gitignore is respected on top.
Tiers
| Free (MIT core) | Pro ($9/mo) | Team ($29/seat) | |
|---|---|---|---|
| Framework packs | Python, JS/TS | + React, Flutter, Java, Kotlin, Go, Rust, C#, Swift, Ruby, Elixir, PHP, Solidity | all Pro packs |
| History compaction | — | ✓ | ✓ |
Scheduler (claude -p cron) | — | ✓ | + work-stealing across providers |
| Audit log + secret redaction + policy | — | — | ✓ |
See PRICING.md. Behavior-changing or data-sharing features
(scheduler, work-stealing, telemetry) are off by default and require explicit
opt-in. Display-only features (dollar-value savings) default on.
Monorepo layout
| Package | Purpose | Published |
|---|---|---|
packages/core | MCP server + free packs | npm (MIT) |
packages/init | npx @ai-optimizer/init config + savings preview | npm |
packages/sdk | definePack plugin SDK | npm |
packages/context-mode-import | Import .contextmode configs | npm |
packages/pro | Pro/Team packs + scheduler + audit | private |
apps/landing, apps/dashboard, apps/vscode-extension, apps/license-server | Site, local dashboard, IDE widget, license issuance | private |
tools/pack-bench | Pack quality benchmark harness | private |
Architecture details: ARCHITECTURE.md.
Development
npm install # at repo root (workspaces)
npm run build # build all packages
npm test # run all test suites
Security
Local-only by design — license validation is the only network call. Report
vulnerabilities per SECURITY.md.
License
Core engine is MIT — see LICENSE. Pro/Team packs are proprietary.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.